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What is ai-evaluation-tools?

aglio-lab/ai-evaluation-tools — explained in plain English

Analysis updated 2026-05-18

2PythonAudience · developerComplexity · 1/5LicenseSetup · easy

In one sentence

A curated, monthly reviewed directory of 300+ open source and commercial tools for evaluating LLMs, RAG pipelines, and AI agents.

Mindmap

mindmap
  root((repo))
    What it does
      Curated tool directory
      300 plus entries
      29 categories
    Tech stack
      Python
      JSON CSV data
    Use cases
      Find eval tools
      Compare platforms
      Programmatic lookup
    Audience
      LLM developers
      AI researchers

Code map

Detail Auto

An interactive map of this repo's files and how they connect — its source is parsed live in your browser. Click Visualize to build it.

filefunction / class

What do people build with it?

USE CASE 1

Find the right tool category for evaluating a RAG pipeline, agent, or voice AI system

USE CASE 2

Compare open source versus commercial evaluation platforms before choosing one

USE CASE 3

Pull the machine readable tools.json or tools.csv data into your own script or database

USE CASE 4

Look up which tools handle red teaming, guardrails, or hallucination detection

What is it built with?

PythonJSONCSV

How does it compare?

aglio-lab/ai-evaluation-tools0-bingwu-0/live-interpreter010zx00x1/faresnipe
Stars222
LanguagePythonPythonPython
Setup difficultyeasymoderateeasy
Complexity1/52/52/5
Audiencedevelopergeneralgeneral

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 5min
CC0: the content is placed in the public domain, free to reuse for any purpose with no restrictions.

So what is it?

This repository is a large curated directory of software for evaluating AI systems, covering more than 300 open source and commercial tools organized into 29 categories. It is not a piece of software you install and run, but a reference list, similar in spirit to other "awesome list" style repositories on GitHub, aimed at people who need to figure out which existing tool fits a specific evaluation problem for a large language model, a retrieval based application, or an AI agent. The list is organized around what a reader is trying to do rather than just alphabetically. A table near the top maps common goals, such as testing an AI agent, tracing a production LLM app, checking for jailbreaks, detecting hallucinations, scoring outputs with another model acting as a judge, comparing foundation models, or benchmarking inference speed, to the relevant section of the list. From there the document expands into dedicated sections covering full evaluation platforms, code based evaluation frameworks, cloud provider services, observability and tracing tools, red teaming and guardrail tools, benchmark suites for coding and agents, multilingual and multimodal evaluation, synthetic data generation, and human annotation tools, among others. Each entry links back to its original source, whether that is a GitHub repository, an official product page, or a research paper, so a reader can verify claims rather than take the list's word for it. Entries are also marked with simple icons showing whether something is open source, open weights, an open core product with a paid layer on top, or fully commercial and closed. The whole catalog is also available in machine readable form as JSON and CSV files for anyone who wants to process it programmatically rather than read it as a document. The project describes itself as reviewed monthly and states a last reviewed date of mid July 2026. It is released under the CC0 license, meaning the content is placed in the public domain with no restrictions on reuse. It has 2 stars and is maintained primarily in Python. The full README is longer than what was shown.

Copy-paste prompts

Prompt 1
Using this list, recommend a few open source tools for evaluating a RAG pipeline I'm building.
Prompt 2
Help me compare full stack evaluation platforms versus code based evaluation frameworks from this list.
Prompt 3
Load data/tools.json from this repo and filter it down to LLM observability tools.
Prompt 4
Which entries in this list are best suited for red teaming an LLM app for jailbreaks?

Frequently asked questions

What is ai-evaluation-tools?

A curated, monthly reviewed directory of 300+ open source and commercial tools for evaluating LLMs, RAG pipelines, and AI agents.

What language is ai-evaluation-tools written in?

Mainly Python. The stack also includes Python, JSON, CSV.

What license does ai-evaluation-tools use?

CC0: the content is placed in the public domain, free to reuse for any purpose with no restrictions.

How hard is ai-evaluation-tools to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is ai-evaluation-tools for?

Mainly developer.

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